Rick Johannes Mourits

Historical morbidity data from past epidemics and pandemics are often sparsely or not available at the individual level. As a result, most studies rely on mortality data to assess the dynamics and severity of epidemics or to examine demographic and social disparities. Although mortality inarguably reflects the severity of an epidemic, it only tells half the story, and a comprehensive understanding requires consideration of both morbidity and mortality. This paper harmonizes morbidity data across different administrative levels and demonstrates how spatial analysis can be used to examine demographic and socioeconomic differences between morbidity and mortality. Linking aggregated data to explanatory factors at the ecological level and applying spatial regression analysis enables the investigation of disparities between morbidity and mortality even in the absence of individual-level data. The findings indicate that the factors shaping morbidity patterns differ from those influencing mortality, underscoring the importance of jointly examining both dimensions to fully understand pandemic dynamics. Hence, this paper encourages historical demographers and historical epidemiologists to consider studying morbidity data rather than dismissing it due to perceived limitations in data quality.

One of the biggest challenges in the transition to open science is making data interoperable. Ideally, existing schemas and vocabularies are (re-)used to describe data, but these are generally problematic for historical data, as they exclude historical concepts and are insensitive to temporal variations in meaning. Therefore, the subdiscipline of historical demography has designed its own schemas and vocabularies to standardize historical data, as researchers require them to make and study large-scale reconstructions of populations and life courses. We introduce a web environment called CLAIR-HD that helps researchers to find vocabularies to standardize historical demographic data, and determine lacunae in the standardization of data within the field of historical demography.

Reconstruction of historical persons and family ties is the bread and butter of many researchers and genealogists. With the increasing digital availability of historical person records, the scope and depth of person reconstructions speaks to the imagination of researchers and genealogists. Yet, the lack of standardisation in the description of historical person data has hurt the interoperability and sustainability of both small and large databases. Persons in Context, or PiCo, presents a data model for historical person records within the Resource Description Framework (RDF). RDF or Linked Data is specifically designed for clear, unambiguous information exchange between multiple parties over the internet. We show how reuse of existing ontologies and concentric description are the building blocks of a flexible, straightforward, and stringent data model that emphasises provenance.

The slavenregisters or slave registers of Suriname offer a unique perspective on the social and demographic history of a people in bondage. Thanks to a citizen science project, the archival sources were transcribed in 2017 by hundreds of volunteers. The transcriptions were used to create a longitudinal database of more than 90,000 enslaved persons. This paper describes the sources, data entry, and cleaning to create a standardized database as well as the matching needed to construct life courses. We discuss the best practices we have learned along the way. Finally, it offers prospects for research and expansion of the database to other population sources and areas.

LINKS stands for 'LINKing System for historical family reconstruction' and is a software system to link nominal data from the Dutch archives and ultimately reconstruct historical individuals and families. We present the background and philosophy of this matching system and explain its data structure and functioning. Currently the core data of the LINKS system consists of indexed civil certificates. These certificates are available from 1812 — the start of the Dutch Vital Registration — until the year they are confidential based on privacy laws. For more than 20 years, thousands of volunteers have been working to build this index, which contains not only the names of newborn, married and deceased persons, but also the names of their parents, places of birth, ages and sometimes their occupational titles. The software system LINKS includes the standardization of all input before linking, nominal record linkage procedures and identification of all unique persons involved in the system. All processes are repeatable and a strict distinction is maintained between source data, standardized, linked and enriched data and released data. Moreover, LINKS also informs archives about all kinds of errors and inconsistencies found during the cleaning and matching process. We will discuss two matching systems, the first is the original querying system that runs within a MySQL database environment and the second is a newly developed system, called burgerLinker, which is based on knowledge graphs and which is designed as a system that can be used independently from LINKS and is made available as open source software. Finally, we present the most important releases of LINKS data so far: two national releases that link birth and parental marriage certificates, creating families and pedigrees and an integrated dataset of persons, families and family trees in four provinces.

The European Experience brings together the expertise of nearly a hundred historians from eight European universities to internationalise and diversify the study of modern European history, exploring a grand sweep of time from 1500 to 2000.

Are daughters of older mothers less fertile? The human mutation rate is high and increases with chronological age. As female oocytes age, they become less functional, reducing female chances at successful reproduction. Increased oocyte mutation loads at advanced age may be passed on to offspring, decreasing fertility among daughters born to older mothers. In this paper we study the effects of maternal ageing on her daughter's fertility, including total number of children, age at last birth, and neonatal mortality among her children. We study fertility histories of two generations of women from mutually exclusive families from a pre-demographic transition historical population in the Dutch province of Zeeland. Using mixed effect Poisson and linear models to take within family (sibling) relations into account, we show that among married daughters fertility is reduced for those who were born to mothers with an advanced maternal age, resulting in fewer children ever born and earlier ages at last birth. We do not find consistent evidence for effects on neonatal mortality. These results may indicate that women born to older mothers are negatively affected by their mothers' increased age.

A century ago, the 1918–19 influenza pandemic swept across the globe, taking the lives of over 50 million people. We use data from the Dutch civil registry to show which regions in the Netherlands were most affected by the 1918–19 pandemic. We do so for the entire 1918 year as well as the first, second, and third wave that hit the Netherlands in summer 1918, autumn 1918, and winter 1919. Our analyses show that excess mortality was highest in Oost-Brabant, Zuid-Limburg, Noord-Holland, and Drenthe, Groningen, and Overijssel, whereas excess mortality was low in Zuid-Beveland, the Utrechtse Heuvelrug, and the Achterhoek. Furthermore, neighboring municipalities resembled one another in how severely they were affected, but only for the second wave that hit the Netherlands in autumn 1918. This non-random spatial distribution of excess mortality in autumn 1918 suggests that regional differences affected the spread of the disease.